Abstract—In this paper, we propose the method to extract
objects with excessive disparities in 3D stereoscopic images
using cost function considering the intensity and the depth
information. The traditional region segmentation method such
as CLRG (Centroid Linkage Region Growing) used in the
general 2D images is processed only based on intensity
information. 3D stereoscopic images have the additional
information that is depth. In the proposed method, first the
excessive disparity candidate regions are decided using the
pre-defined threshold in the disparity-map. Next the extracted
excessive disparity candidate regions are labeled to object
regions and the other regions are labeled to background regions.
The regions labeled as object are set as region that will be
segmented in 3D stereoscopic left image. The proposed
segmentation method considering the intensity and the depth is
applied to these regions in 3D stereoscopic left image. Finally to
eliminate small regions, the morphological filter is used.
Index Terms—3D Stereoscopic images, binary, disparities,
region-based segmentation, discomfort and fatigue, cost
function.
S. H. Kim is with the Department of Computer Engineering of the
University of Young-San at Yangsan, Kyungnam (e-mail: ksh50@
ysu.ac.kr).
J. Y. Kim is with the School of Undeclared Majors, University Collage of
the University of Young-San at Busan (e-mail: neocopy@ ysu.ac.kr).
G. J. So is with the Department of Cyber & Police Science of the
University of Young-San at Yangsan, Kyungnam (e-mail: kjso@ ysu.ac.kr).
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Cite:Sang Hyun Kim, Jeong Yeop Kim, and Gil Ja So, "Object Extraction with Excessive Disparities in 3D Stereoscopic Images," International Journal of Computer Theory and Engineering vol. 6, no. 4, pp. 313-318, 2014.
